This disclosure provides an image processing method and system for recognizing barcodes and/or product labels. According to an exemplary embodiment, the method uses a multifaceted detection process that includes both image enhancement of a candidate barcode region and other product label information associated with a candidate barcode region to identify a product label, where the candidate barcode region includes a nonreadable barcode. According to one exemplary application, a store profile is generated based on the identifications of the product labels which are associated with a location of a product within a store.
This disclosure also relates to product mapping and finds particular application in connection with a system and method for determining the spatial layout of product content of a product facility, such as a store.
Retail chains, such as pharmacy, grocery, home improvement, and others, may have a set of product facilities, such as stores, in which products are presented on product display units, such as shelves, cases, and the like. Product information is generally displayed close to the product, on preprinted product labels. The product labels indicate the price of the item and generally include a unique identifier for the product, e.g., in the form of a barcode, which is often used by the store for restocking and other purposes. Periodically, stores place some of the items on sale, or otherwise adjust prices. This entails printing of sale item labels and/or associated signage and manual replacement of the product labels and/or addition of associated signage. The printing and posting of such sale item signage within each store often occurs at weekly intervals.
It would be advantageous to each store if the signage was printed and packed in the order in which a store employee encounters the sale products while walking down each aisle. However, retail chains generally cannot control or predict the product locations across each of their stores. This may be due to a number of factors, such as store manager discretion, local product merchandising campaigns, different store layouts, and so forth. Thus, individual stores may resort to manually pre-sorting the signage into the specific order appropriate for that store, which can be time consuming and not always accurate.
Copending patent applications U.S. patent application Ser. No. 14/303,809, filed Jun. 13, 2014, by Wu et al., and entitled “Store Shelf Imaging System” and U.S. patent application Ser. No. 14/303,735, filed Jun. 13, 2014, by Wu et al., and entitled “Method and System for Spatial Characterization of Imaging System” provide a method and system for a chain of stores to be able to collect product location data automatically across its stores. Each store could then receive signage which has been automatically packaged in an appropriate order to avoid a pre-sorting step.
There exist many prior arts on barcode detection and/or recognition, see Péter Bodnár and László G. Nyúl, “Improving Barcode Detection with Combination of Simple Detectors,” 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (2012) and J. Liyanage, “Efficient Decoding of Blurred, Pitched, and Scratched Barcode Images,” Second International Conference on Industrial and Information Systems (ICIIS 2007), August, (2007), and citations of them. They can perform quite well with sufficient image resolution and high image quality (no motion blur, no out of focus, good and uniform illumination . . . ). In practice, high quality imaging is not always feasible or affordable. As a result, barcode recognition is still a fairly active research area focusing on solving real-world problems even though it may seem straightforward. See Péter Bodnár and László G. Nyúl, “Improving Barcode Detection with Combination of Simple Detectors,” 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (2012) and J. Liyanage, “Efficient Decoding of Blurred, Pitched, and Scratched Barcode Images,” Second International Conference on Industrial and Information Systems (ICIIS 2007), August, (2007). For a retail application as disclosed in U.S. patent application Ser. No. 14/303,809 filed Jun. 13, 2014, by Wu et al., and entitled “Store Shelf Imaging System”, high throughput and broad spatial coverage, i.e., the entire store, are required where 15000 barcodes or more covering the entire store need to be recognized in a relatively short time-frame, e.g., 4-8 hours. This makes the matter worse since maintaining high quality imaging over a large spatial area while achieving such throughput is not a simple task. Hence improvement on existing barcode detection and recognition methods is needed.